Tumor grading from blood volume maps

Abstract

An embodiment of the invention is to make possible a non-invasive grading of a tumor based on parameters determined from a frequency distribution (histogram) of values in a map representing cerebral blood volume (CBV) or cellular metabolism in the tumor. The method is especially applicable to brain tumors such as gliomas where histological grading is difficult. The invention provides a precise and consistent grading since it relies on values selected from the whole tumor (not just from hot spots); since it takes the diversity or heterogeneity of the vascularization into account by analyzing the frequency distribution (not just a mean value); and since it involves and allows for a more automated procedure wherein any subjective contributions from human operators is not critical to the resulting grading. CBV maps may be obtained by perfusion imaging using MRI or CT scanning. Cellular metabolism maps may be obtained from a glucose metabolism map obtained by positron emission tomography (PET).

1. A computer implemented method for grading malignancy of a tumor, comprising
 receiving electronic data comprising a map of values defining perfusion, blood volume, or cellular metabolism in a tumor of a subject; 
 storing in an electronic memory, a plurality of value intervals, and counting with an electronic processor the number of values within selected regions of the map that are within each of a plurality of defined value intervals to determine a frequency distribution of values in the selected regions; 
 assessing a tumor malignancy based on the frequency distribution, where a more heterogeneous distribution corresponds to a higher malignancy; and 
 transmitting tumor assessment data based, at least in part, on the assessment of the tumor malignancy to an output device. 
 
     
     
       2. The method according to  claim 1 , wherein the tumor malignancy assessment is based on one or more of the following parameters determined from the frequency distribution:
 a parameter descriptive of a shape of the frequency distribution, 
 variables in a parametric model applied to the frequency distribution; 
 a highest relative fraction of values in one interval; 
 whether the distribution exceeds a predetermined threshold value; or 
 a FWHM or similar value of the frequency distribution. 
 
     
     
       3. The method according to  claim 1 , wherein the map of values is a blood volume map obtained by perfusion imaging using an intravascular contrast agent. 
     
     
       4. The method according to  claim 1 , wherein the map of values is a glucose metabolism map obtained by positron emission tomography (PET). 
     
     
       5. The method according to  claim 1 , wherein assessing the tumor malignancy comprises determining a shape of the frequency distribution and comparing with previously determined shapes of equivalent frequency distributions from tumors with a known malignancy assessment. 
     
     
       6. The method according to  claim 1 , wherein the entire tumor is selected to be applied in the malignancy assessment. 
     
     
       7. The method according to  claim 1 , further comprising normalizing the frequency distribution to enable comparison between frequency distributions of different tumors. 
     
     
       8. The method of  claim 1 , further comprising selecting regions of the tumor whose corresponding values in the map are to be applied in the grading. 
     
     
       9. The method according to  claim 8 , further comprising normalizing or standardizing values of at least the selected regions of the tumor to a reference value. 
     
     
       10. The method of  claim 1 , wherein the output device is an electronic display, a printer, a data bus, or a network connection. 
     
     
       11. The method of  claim 1 , further comprising receiving tumor image data from an input device, wherein the map of values is derived from the tumor image data. 
     
     
       12. The method of  claim 11 , wherein the tumor image data is generated by a CT, MR, or PET scanner. 
     
     
       13. A system for grading malignancy of tumors, the system comprising:
 a receiver configured to receive a map of values defining perfusion, blood volume, or cellular metabolism of a tumor of a subject; 
 software configured to co-register the map of values with image data representing tissue type of a tumor region; 
 a data selection tool configured to electronically assist an operator in selecting regions of the tumor whose corresponding values in the map are to be applied in the grading; 
 software configured to count the number of values of the selected regions within each of a plurality of value intervals to determine a frequency distribution of values in the selected regions; 
 software for determining one or more parameters from the frequency distribution related to heterogeneity of the frequency distribution; and 
 a transmitter configured to transmit parameter data derived, at least in part, from the one or more parameters to an output device. 
 
     
     
       14. The method according to  claim 13 , wherein the software for determining one or more parameters comprises means for correlating said one or more parameters with a malignancy of the tumor, where the more heterogeneous frequency distribution corresponds to a higher malignancy grade. 
     
     
       15. The system of  claim 13 , further comprising an image data receiver for receiving tumor image data. 
     
     
       16. The system of  claim 15 , wherein the tumor image data is generated by a CT, MR, or PET scanner. 
     
     
       17. The system of  claim 15 , wherein the image data receiver is an image recording apparatus such as a CT, MR, or PET scanner. 
     
     
       18. The system of  claim 15 , wherein the image data receiver is an internal or external storage. 
     
     
       19. The system of  claim 13 , wherein the transmitter is configured to transmit data to a printer, a display, a data bus, or a network connection. 
     
     
       20. The system of  claim 15 , wherein the image data receiver is a data bus allowing access to a memory, an internet connection, or a cable or wireless connection. 
     
     
       21. A method for preparing a correlation data set for use in grading the malignancy of a tumor, comprising:
 receiving electronic data comprising a plurality of maps of values defining perfusion, blood volume, or cellular metabolism in a plurality of tumors; 
 selecting a set of tumors of similar type so that the set comprises tumors of all malignancies; 
 storing in an electronic memory, a histologically determined malignancy of each tumor in the set; 
 for each tumor in the set: 
 selecting regions of the tumor whose corresponding values in the map of values are to be applied in the grading; 
 storing, in an electronic memory, a plurality of value intervals and counting with a processor circuit, the number of values of the selected regions within each interval to determine a frequency distribution of values in the selected regions; 
 determining, with a processor circuit, one or more parameters characterizing the heterogeneity of the frequency distribution; and 
 correlating the determined parameters with the histological determined malignancies to prepare a correlation data set from which a malignancy can be estimated for another tumor of similar type using corresponding parameters obtained from this other tumor. 
 
     
     
       22. The method of  claim 21 , further comprising transmitting correlation data derived, at least in part, from the correlation data set to an output device. 
     
     
       23. The method of  claim 22 , wherein the output device is an electronic display, a printer, a data bus, or a network connection. 
     
     
       24. The method of  claim 21 , further comprising receiving tumor image data from an input device, wherein the map of values is derived from the tumor image data. 
     
     
       25. The method of  claim 24 , wherein the tumor image data is generated by a CT, MR, or PET scanner.